Introduction to Sparse Matrices in Scilab

Abstract

The goal of this document is to present the management of sparse matrices in Scilab. We present the basic features of Scilab, which allows to create sparse matrices and to convert from and to dense matrices. We show how to solve sparse linear equations in Scilab, by using sparse LU decomposition and iterative methods. We present the sparse Cholesky decomposition. We present the functions from the UMFPACK and TAUCS modules. We briefly present the internal sparse API. We introduce to the Arnoldi package. We present the Matrix Market external module. This document is a draft.

Authors

• Copyright (C) 2008-2011 - Consortium Scilab - Digiteo - Michael Baudin

Licence

This document is released under the terms of the Creative Commons Attribution-ShareAlike 3.0 Unported License :

http://creativecommons.org/licenses/by-sa/3.0/

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